Founding AI Engineer
15 hours ago
Novyte Materials is building a frontier AI engine for materials discovery, a system that learns the structure, physics and governing rules of matter, and uses that intelligence to propose entirely new materials for real-world synthesis.
We operate at the intersection of
machine learning, scientific computing and materials physics
, where datasets are sparse, search spaces are astronomical, and model decisions directly influence real laboratory experiments.
If you want to work on AI systems that
reason about the physical world,
not ad ranking, recommendation systems or standard NLP, this is the place.
Location : Mumbai/Bangalore
Role Description
We are hiring a
Founding AI Engineer
to design and build the core intelligence layer of Novyte's platform. This is an on-site role in Mumbai/Bangalore, working closely with the founder.
You will architect generative, predictive and physics-aware ML models that operate across multimodal scientific data: graphs, crystal structures, text, spectra, simulations and high-dimensional descriptors. Your work will meaningfully shape the technical DNA of the company.
This is a founder-level role with end-to-end ownership. You will:
- Design next-gen ML architectures (GNNs, Transformers, Diffusion-style models)
- Build physics-aware representation learning systems
- Develop active learning and RL-based exploration loops
- Create scalable training pipelines and distributed training workflows
- Integrate ML models with first-principles simulation and scientific data
- Define foundational research practices, abstractions and model standards
- Work cross-functionally with computational chemists, platform engineers and research partners
This is not a routine AIML job. You will work in a frontier scientific domain with deep ambiguity, high complexity and massive real-world impact.
Qualifications
Required
- Strong experience with PyTorch or JAX
- Expertise in graph learning, geometric deep learning, or multimodal ML
- Experience with RL, active learning or uncertainty-aware modeling
- Strong engineering fundamentals (clean abstractions, reproducibility, systematic debugging)
- Experience working with noisy, sparse or non-standard scientific datasets
- Ability to read research papers, build prototypes quickly and reason from first principles
- Interest in ML for scientific domains, not generic applied ML
Bonus
- Experience with diffusion models, flow matching or generative modeling
- Knowledge of materials science, physics-informed ML or simulation-integrated ML
- Familiarity with HPC, large-scale training or hybrid compute workflows
- Research publications or open-source contributions
- Prior startup or founding experience
What Novyte Offers
- Founding-level ownership and ability to define core IP
- A chance to build the intelligence core of a scientific discovery engine
- Deep, technical work with clear milestones and real-world validation
- A research-driven environment with full autonomy over modeling direction
- Direct impact, your models inform real lab experiments within months
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